Using satisfaction analysis to predict decision quality

Detalhes bibliográficos
Autor(a) principal: Carneiro, João
Data de Publicação: 2015
Outros Autores: Marreiros, Goreti, Novais, Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/50524
Resumo: One of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. The amount of GDSS incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. To create the model some assumptions are deducted from literature, as well as the premises needed to validate any decision satisfaction model. This model is intended to enable the understanding of the decision’s quality achieved with an argumentation system and to evaluate its capability to potentiate the decision’s quality. The proposed model validates all the assumptions found in the literature regarding the participant’s satisfaction.
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spelling Using satisfaction analysis to predict decision qualityDecision SatisfactionGroup Decision Support SystemsOutcomesAffective ComputingEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaOne of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. The amount of GDSS incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. To create the model some assumptions are deducted from literature, as well as the premises needed to validate any decision satisfaction model. This model is intended to enable the understanding of the decision’s quality achieved with an argumentation system and to evaluate its capability to potentiate the decision’s quality. The proposed model validates all the assumptions found in the literature regarding the participant’s satisfaction.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEISII/1386/2012) and SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersionCESER PublicationsUniversidade do MinhoCarneiro, JoãoMarreiros, GoretiNovais, Paulo20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/50524engCarneiro J., Marreiros G., Novais P., Using Satisfaction Analysis to Predict Decision Quality, International Journal of Artificial Intelligence (IJAI), CESER Publications, ISSN 0974-0635, Volume 13, Nº 1, pp 45-57, 2015.0974-0635http://www.ceser.in/ceserp/index.php/ijai/article/view/3525info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:37:30Zoai:repositorium.sdum.uminho.pt:1822/50524Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:33:49.164875Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Using satisfaction analysis to predict decision quality
title Using satisfaction analysis to predict decision quality
spellingShingle Using satisfaction analysis to predict decision quality
Carneiro, João
Decision Satisfaction
Group Decision Support Systems
Outcomes
Affective Computing
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short Using satisfaction analysis to predict decision quality
title_full Using satisfaction analysis to predict decision quality
title_fullStr Using satisfaction analysis to predict decision quality
title_full_unstemmed Using satisfaction analysis to predict decision quality
title_sort Using satisfaction analysis to predict decision quality
author Carneiro, João
author_facet Carneiro, João
Marreiros, Goreti
Novais, Paulo
author_role author
author2 Marreiros, Goreti
Novais, Paulo
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Carneiro, João
Marreiros, Goreti
Novais, Paulo
dc.subject.por.fl_str_mv Decision Satisfaction
Group Decision Support Systems
Outcomes
Affective Computing
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic Decision Satisfaction
Group Decision Support Systems
Outcomes
Affective Computing
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description One of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. The amount of GDSS incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. To create the model some assumptions are deducted from literature, as well as the premises needed to validate any decision satisfaction model. This model is intended to enable the understanding of the decision’s quality achieved with an argumentation system and to evaluate its capability to potentiate the decision’s quality. The proposed model validates all the assumptions found in the literature regarding the participant’s satisfaction.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/50524
url http://hdl.handle.net/1822/50524
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Carneiro J., Marreiros G., Novais P., Using Satisfaction Analysis to Predict Decision Quality, International Journal of Artificial Intelligence (IJAI), CESER Publications, ISSN 0974-0635, Volume 13, Nº 1, pp 45-57, 2015.
0974-0635
http://www.ceser.in/ceserp/index.php/ijai/article/view/3525
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CESER Publications
publisher.none.fl_str_mv CESER Publications
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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